1. Technical Field
The present teaching relates to methods, systems, and programming for Internet services. Particularly, the present teaching is directed to methods, systems, and programming for search suggestion.
2. Discussion of Technical Background
Online content search is a process of interactively searching for and retrieving requested information via a search application running on a local user device, such as a computer or a mobile device, from online databases. Online search is conducted through search engines, which are programs running at a remote server and searching documents for specified keywords and return a list of the documents where the keywords were found. Known major search engines have features called “search suggestion” designed to help users narrow in on what they are looking for. For example, as users type a search query, a list of query suggestions that have been used by many other users before are displayed to assist the users in selecting a desired search query.
However, existing search engines focus on how to discover relevant queries from query logs without considering users' current search behavior, which is very important in many scenarios. Traditional search suggestion systems have three common features: (1) suggestion database is generated by mining search logs and combining other knowledge databases; (2) personal suggestion database contains user's search history in the past; and (3) query suggestion is based on user's prefix input in the search box. As described by these features, query suggestions in the known solutions mainly come from general users' past search behavior, which ignores a specific user's immediate previous query in the same user session as context. On the other side, users' immediate previous query is very important, since users' intent or interests are explicitly expressed in previous search.
Therefore, there is a need to provide an improved solution for search suggestion to solve the above-mentioned problems.